EP2011080B1 - Bildanalyse - Google Patents

Bildanalyse Download PDF

Info

Publication number
EP2011080B1
EP2011080B1 EP07732500.9A EP07732500A EP2011080B1 EP 2011080 B1 EP2011080 B1 EP 2011080B1 EP 07732500 A EP07732500 A EP 07732500A EP 2011080 B1 EP2011080 B1 EP 2011080B1
Authority
EP
European Patent Office
Prior art keywords
block
values
spatial
filtered
image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Not-in-force
Application number
EP07732500.9A
Other languages
English (en)
French (fr)
Other versions
EP2011080A2 (de
Inventor
Jonathan Diggins
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Snell Advanced Media Ltd
Original Assignee
Snell Advanced Media Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Snell Advanced Media Ltd filed Critical Snell Advanced Media Ltd
Publication of EP2011080A2 publication Critical patent/EP2011080A2/de
Application granted granted Critical
Publication of EP2011080B1 publication Critical patent/EP2011080B1/de
Not-in-force legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
    • H04N19/86—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression involving reduction of coding artifacts, e.g. of blockiness
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/61—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding in combination with predictive coding

Definitions

  • This invention concerns image analysis of video signals or data in order to detect prior, block-based processing, and to quantify block-related picture impairments.
  • Video quality analysis methods fall into two types: “double-ended” methods where the processed images are compared with unprocessed images to identify artefacts; and, “single-ended” methods in which the processed images are analysed without reference to unprocessed images. Double-ended methods are usually only applicable to a research and development environment; single-ended methods are preferable in normal commercial production and distribution operations.
  • blockiness or block artefacts are a measure of the subjective impairment of the images due to the block-based processing.
  • these methods require prior knowledge of the positions of the block boundaries or the size of the blocks. For example: if the boundary positions are known, average luminance or chrominance differences can be evaluated across the boundaries; and, if the size of the blocks is known, inter-pixel differences can be evaluated in a repeating pattern with a periodicity equal to the block size.
  • a digital image processing method determining the extent of contouring artifacts in the digital image includes the steps of: forming a column difference image; averaging the values in the columns in the column difference image to produce a column difference array; computing the average of the values in the column difference array that are separated by one block width to produce a block averaged column difference array; locating the peak value in the block averaged column difference array; repeating the above mentioned steps in the row direction; locating block boundaries based on the locations of peak values of column and row difference arrays; calculating DC value for each block; generating a histogram of the block DC values; calculating the Fourier transform of the histogram; locating the first non-DC peak in the Fourier transform domain; calculating a DC quantization step size based on the frequency of the first non-DC peak; and, employing the DC quantization step size as a measure of the extent of the contouring artifacts in the digital image.
  • EP 1 003 335 discloses a method of efficient and reliable detection of error blocks in a DCT-based compressed video sequence extracts edges from an image that correspond to the DCT blocks. These edges are processed to determine an edge energy value. The edge energy value is compared with a threshold to provide an alarm for an error block when the threshold is exceeded. The edge energies for each block may be summed and compared with an overall threshold value to generate the alarm, or the edge energy for each edge may be compared with an edge threshold value to determine which are good and which are suspect, with the alarm being set when at least three of the edges are suspect (two edges for corner blocks).
  • the invention comprises a novel method of image analysis in which block-based artefacts can be quantified, and the size of processing blocks measured, without having prior access to the unprocessed image.
  • the invention consists, in one aspect, method of analysing image data to quantify artefacts due to block-based processing in which a set of pixel values derived from said image data is spatially filtered and rectified and one or more impairment parameters are derived from the said filtered and rectified values.
  • said filter is a high-pass filter which may be set to pass only frequencies which are likely to contain block edge information.
  • said filter is a band-pass filter to exclude higher frequencies which may represent noise, in the context of block based processing.
  • said filter is selected automatically from two or more alternative filters the selection depending on a comparison between respective rectified filter outputs.
  • an inverse coring function is applied to the rectified data.
  • a block size parameter may be derived from analysis of the spatial frequency spectrum of the filtered and rectified data.
  • a block size parameter may be derived from analysis of a two dimensional autocorrelation function of the filtered and rectified data.
  • a block-artefact presence parameter may be derived, in one example by the steps of:
  • said filtered and rectified data is summed vertically or horizontally over substantially the full image height or width prior to the said impairment parameter derivation.
  • An impairment parameter may be derived from an autocorrelation function of the said summed data.
  • a block size parameter may be derived from the distance between peaks in the said autocorrelation function or from a discrete cosine transform of the said autocorrelation function.
  • One or more basis functions of the said discrete cosine transform may be chosen to correspond to expected block spatial frequencies.
  • the autocorrelation function may be filtered by a spatial band-pass filter.
  • the autocorrelation function may be filtered by a temporal low-pass filter which combines data from two or more images in a sequence of images.
  • Block size parameters from more than one image may be combined; the combination may be a modal value.
  • Block edge positions may be identified by the steps of:
  • An identified block edge location may be modified by the steps of:
  • the present invention consists in a method of determining a block artefact measure for an image region comprising the steps of:
  • the number of identified block-edge positions within the said region at which block edges are identified is added to the said block interior difference sum before dividing it into the said block-edge difference sum to form the block artefact measure.
  • the block artefact measure is weighted by an average luminance value so that the artefact measure is attenuated in areas of very high and very low average luminance.
  • a block artefact measure for an image may be formed by combining one or more of the highest respective regional artefact measures and discarding other regional artefact measures.
  • Artefact measures for images in a sequence may be combined in a temporal low-pass filter.
  • the artefact measure may be expressed as a logarithm.
  • a block artefact measure is derived from the variation in block artefact measure of an image sequence over a sequence of images.
  • the variation in block artefact measure of an image sequence may be analysed to identify a repeating pattern of picture coding methods.
  • the invention may be used to analyse image data representing values associated with pixels of an image.
  • the values may represent luminance, colour difference (e.g. C B or C R ), primary colour component (e.g. R, G or B) or any other convenient pixel parameter.
  • Analogue video signals may be sampled to obtain pixel values for analysis.
  • a sequence of values corresponding to adjacent pixels (1) is input to a high-pass filter (2).
  • a sequence of horizontally adjacent pixels is used, such as the stream of luminance values from alternate words of an ITU-R Rec. 656 digital interface signal, or successive samples of video waveform sampled at a multiple of its line frequency.
  • a stream of values corresponding to vertically adjacent pixels can be input so as to analyse the vertical component of the block structure. If the image was scanned with an interlaced raster vertically adjacent pixels may be from adjacent fields.
  • the sequence of pixel values (1) may include non-picture values such as blanking and synchronisation data values. These regions comprise only a minority of the total pixels in an image to be analysed and so it is usually unnecessary for them to be excluded.
  • the block structure can become visible as an image artefact because the spatial frequency response of the transmission system varies from block to block. This difference in the spatial frequency response between blocks is most marked at high frequencies.
  • the high pass filter (2) in the exemplary embodiment is used to select the high frequency spatial components of the input signal for further analysis.
  • the high-pass filter (2) may conveniently be implemented in known manner by a Finite Impulse Response (FIR) transversal filter.
  • FIR Finite Impulse Response
  • a suitable filter cut off frequency for luminance signals sampled at 13.5 MHz according to ITU-T Recommendation 601 is 5 MHz.
  • the filter output is rectified by a rectifier (3), which gives an output equal to the magnitude of its input.
  • the expression is evaluated for values of d between unity and at least the largest expected block dimension. Where a sequence of horizontally-adjacent pixels from MPEG-2 decoded video is analysed, a convenient range of values of d is one to 32.
  • the correlation processor (4) receives a summation window signal (5) which identifies the set of pixels to be included in the summation.
  • the summation need not necessarily exclude blanking and synchronisation data and so the summation window signal can be a simple once-per-field reset of the summation.
  • the summation will include pixels from more than one field and the exact nature of the summation window signal (5) will depend on the way the access to these fields is arranged.
  • One possibility is for the interlaced image to be written to a frame store and read out as a progressively scanned image. In this case the summation can be reset at the frame rate.
  • the output from the correlation processor (4) is a set of values A( d ) for each summation defined by the summation window signal (5). In a typical process analysing streaming video this output will be a set of 32 values once per field. These sets of values are passed to two analysis processes: a block size analyser (6); and, a block artefact analyser (7).
  • FIG. 2 An example of an output from the correlation processor (4) is shown in Figure 2 .
  • the Figure shows values of d from zero to 30 for illustration, in a practical system a different range of values of d , such as one to 32, may be used.
  • the auto-correlation function A( d ) shows regular peaks and by analysis of the height and pitch (inter-peak distance) of these peaks the magnitude of block artefacts and the block size can be determined.
  • the block size analyser (6) determines the pitch in units of d.
  • d is the distance between successive (filtered and rectified) samples input to the correlation processor (4). This pitch may be converted to the block size, depending on the input sample spacing, and is output (8).
  • the input samples are adjacent pixel values and each unit of d represents one pixel.
  • the block size is eight pixels.
  • One method of operation of the block size analyser (6) is to determine the distance between the two most pronounced local maxima of the auto-correlation function as follows:
  • the block size may not be an integral number of pixels (the image may have been re-scaled by a non-integer scaling factor after block-based processing).
  • the block artefact analyser (7) analyses the heights of the peaks in the auto-correlation function relative to the levels of the intervening troughs, and outputs the result as a block measure output (9).
  • a suitable method is as follows:
  • the block size output (8) and the block artefact measure (9) may be unreliable.
  • greater reliability can be achieved by combining the results of several summations; for example the analysis results from several fields of a video sequence may be combined. This is shown in Figure 1 by including a median filter (10) at the output of the block size analyser (6); and, a recursive (IIR) filter (11) at the output of the block artefact analyser (7).
  • a suitable algorithm for the median filter (10) is to sort the current filter input and an even number of previous filter inputs, two say, into rank order, and select the middle ranking input as the filter output. This value then forms the block-size output (12) from the analyser.
  • the natural correlation of nearby pixels may mask the peaks in the output from the correlation processor (4) and it may be convenient to identify block sizes below a certain size as unreliable, or to inhibit small block size values from being output.
  • a suitable energy value is that obtained by squaring the filter outputs for each pixel and accumulating the results (this is A(0)).
  • a filter other than the filter (2) can be applied to the input pixel values (1) and the output of that other filter squared and used to calculate an energy value.
  • a weighted block artefact measure can be obtained by multiplying one of the previously described metrics by an energy value.
  • block artefacts are more likely to be visible where there is little motion in the picture. Such areas can be identified by taking inter-field differences between co-located pixels and summing the results. Any of the previously described block artefact measures can be multiplied by this sum to give a weighted block artefact measure.
  • the frame-to-frame variation of a block artefact measure can be used to identify the length of the Group-of-Pictures (GoP) cycle. (i.e. The pattern by which directly-coded and various types of prediction-coded frames follow each other.)
  • GoP Group-of-Pictures
  • a low-frequency variation of the block artefact measure can be identified by a low-pass filter and the period of this frequency can be assumed to be the duration of one GoP.
  • a further artefact measure can be derived from the frame-to-frame variation of the block artefact measure; this can give an indication of the subjective impairment of a video sequence due to variation of coding artefacts with time.
  • the invention is not restricted to horizontal or vertical analysis; data from pixels along any straight line in an image can be analysed. In some circumstances (e.g. where the block-size is large relative to the pixel pitch) it may be convenient to spatially sub-sample the pixels prior to processing (with or without associated pre-filtering or interpolation).
  • the invention may be applied in a two dimensional manner by performing a two-dimensional auto-correlation process in the block (4) of Figure 1 and analysing the resulting two-dimensional auto-correlation surface for peaks and troughs.
  • the correlation processor (4) may be simplified by omitting some d values from the summation. For example, d values providing most useful information can be identified by experience in analysing particular types of image data and less-informative d values excluded from the calculation.
  • FIG. 3 A block diagram of a further example of the invention is shown in Figure 3 .
  • An input stream of pixel values (300) is input to a filter (301), which identifies high frequency components. If the images have been up-converted, for example from standard-definition to high-definition, there may not be sufficient high-frequency information at the filter output to analyse.
  • a filter having a lower frequency pass-band such as a non-sharp, band-pass filter centred near the mid-band; i.e. about half the Nyquist frequency.
  • Automatic switching between different filters can be arranged by comparing the rectified output of at least one filter with a threshold and choosing the filter having the highest frequency pass-band containing significant output information.
  • the filtered output is rectified and small-amplitude values selected in a combined rectification and inverse-coring function (302).
  • This function returns the absolute magnitude of low amplitude samples from the filter (301) and progressively attenuates samples whose magnitude exceeds a fixed, low threshold.
  • the resulting set of filtered, inverse-cored and rectified pixel values are summed vertically over each individual image in a summing block (303) to obtain a set of "pixel-column activity" values (304).
  • the set comprises one value for each horizontal pixel location of each image represented by the stream of pixel values (300).
  • An autocorrelation function processor (305) calculates the autocorrelation function of the set of pixel-column activity values (304) from each image.
  • the function should have sufficient range to exceed the widest expected block width by a factor of three or four times; typically, correlation values for inter-sample spacings from zero to at least 100 are calculated.
  • the output (306) of the correlation function (305) for each image will be similar to Figure 2 and will have a periodic variation reflecting the horizontal block structure.
  • the correlation function shown in Figure 2 is treated as a segment of a notional sampled signal, where the vertical axis represents amplitude and the horizontal axis represents spatial position, useful information may be obtained by filtering that notional signal; in particular a band-pass filter can separate out the alternating component due to the block structure. This is done by a band-pass filter (307), which passes the band of spatial frequencies including all expected block sizes and removes lower and higher frequency components.
  • each image will result in a filtered notional signal segment at the output of the filter (307), and these segments will vary with time as the sequence progresses.
  • These temporal variations are smoothed by a low-pass temporal filter (308) which recursively combines corresponding correlation values from succeeding images in the sequence so as to reject short-duration spurious results and obtain a more representative set of notional signal segments.
  • DCT discrete cosine transform
  • Each transform coefficient indicates the magnitude of a respective horizontal block spatial frequency.
  • the basis functions of the transform can be chosen to include expected block sizes, and may include non-integral block sizes; i.e. frequencies which are not integral multiples of the horizontal pixel pitch. Typically about 17 transform coefficients are derived.
  • the sets of transform coefficients from the DCT processor (309) are evaluated in a block size determination process (310) so as to determine the horizontal block size. If, as will usually be the case, the band-pass filter (307) does not have a flat pass-band, the DCT coefficients will need to be corrected according to a window function which "equalises" the filter pass-band response so that each transform coefficient accurately reflects the amplitude of the relevant block spatial frequency.
  • the block size determination process (310) operates by ranking the transform coefficients once per image and finding the three largest values. The largest coefficient is likely to correspond to the block size, or a multiple of the block size. If the set of three values contains values which are multiples of each other, the lowest sub-multiple is retained and the higher discarded.
  • the determined block sizes for several images in a sequence are combined in a histogram and the most frequently reported block size, i.e. the modal value of the set of detected values, is output (311).
  • the function is low-pass filtered (in an analogous way to the band-pass filter (307)) in a low-pass filter (312).
  • the unfiltered autocorrelation function (306) and the outputs from the filters (307) and (312) are processed in a block presence determination function (313) to derive a block presence flag (314).
  • the block presence function (313) detects the condition where the activity of the autocorrelation function (306) is concentrated in the pass-band of the bandpass filter (307).
  • a suitable method is shown in Figure 4 .
  • an input correlation function (406) is band-pass filtered (407) and low-pass filtered (412). (These filters correspond to the filters (307) and (312) of Figure 3 .)
  • Weighted differences between each of the filter outputs and their respective inputs are formed by subtractors (421) and (422). These are rectified in rectifiers (423) and (425); and the unfiltered correlation function is also rectified in a rectifier (424).
  • a weighed combination of the outputs from the three rectifiers is made by the adder (426) and the subtractor (427). This combination is compared with a threshold in a comparator (428) and a block artefact presence flag (414) (equivalent to the flag (314)) is activated when the combination exceeds the threshold.
  • candidate block-edge positions are found by further processing of the pixel-column activity values (304). This is done in a candidate block-edge location process (315), which analyses the data values (304) to determine positions of peak activity separated by a distance equal to the determined block size.
  • the candidate block-edge location process (315) receives an input of the measured block size (311).
  • This size value will be the period of one of the basis functions of the DCT (309), and may not be completely accurate; for example, the basis functions may only include integer values and the actual block size may not be an integer number of pixels.
  • the set of pixel-column activity values (304) for an image is processed as shown in Figure 5 to obtain candidate block-edge positions.
  • members of the set of pixel-column activity values (304) are denoted by Pi, where i is an index value such that the left-most value has the index zero and the right-most value has the index L (i.e. the images are (L + 1) pixels wide).
  • the integer part of the measured block size (311) is denoted by the value B.
  • an analysis phase parameter ⁇ is set to zero in step (501) and then an index variable i is set to the value (B + ⁇ ) in step (502).
  • step (503) the activity values of pairs of pixels separated by one measured block-size are summed to obtain a set of B sum-values. The maximum value of this set is identified and the index value of the right-most pixel contributing to it is noted as a first candidate block-edge position.
  • step (504) the index parameter is incremented by B and step (503) is repeated for the next B activity values.
  • a second candidate block-edge position is then identified from the maximum of this second set of activity values.
  • the steps (503) and (504) are repeated until the right-most pixel column activity value has been included in a sum. This condition is recognised in a test step (505) and the phase parameter ⁇ is incremented by the integer part of one quarter of the measured block size in the step (506).
  • the summing step (503) is then repeated with the starting index increased by the phase increment. This means that further pixel pair sum maxima are selected from blocks of values shifted rightwards. The locations of the maxima are recorded as before.
  • the phase parameter ⁇ is then incremented again and a further set of possible block-edge positions is identified and the phase parameter ⁇ is incremented again in step (506).
  • step (507) The new phase is tested in step (507) to see if it exceeds one half of the measured block size. If this is so, further searches for maxima are not required and the processing moves to step (508) in which index values which have been identified as the location of maxima at two or more analysis phases are confirmed as candidate block-edge positions, and others are discarded.
  • This candidate block-edge location process can be improved by bandpass filtering the pixel-column activity values (304) prior to the location process (315).
  • a filter similar to the filter (307) can be used. Without filtering, block-edges can appear as two closely-spaced peaks in the set of pixel-column activity values (304); this is due to the rectification function of the inverse coring rectifier (302) where a single transient at the output of the filter (301) produces two closely-spaced positive and negative peaks. Filtering combines the two peaks into a single broad peak preceded and succeeded by negative overshoots.
  • the candidate block-edge values from the process (315) are passed to a block-edge location process (316).
  • This process makes use of the actual pixel values (300) and so block edges which extend over less than the full image height can be identified.
  • the process identifies positions close to candidate positions where the difference in value between pixels separated by two pixel pitches is maximum.
  • FIG. 6 A suitable process is shown in Figure 6 .
  • pixel values are denoted by YI where I is an index parameter representing horizontal position in units of one horizontal pixel pitch.
  • I is set to the index of the first candidate position.
  • an evaluation is made, at the position defined by I, of the difference across two pixel pitches, summed for positions one measured block size apart. As shown in the Figure, an equivalent sum value is also calculated for positions one pixel pitch each side of the position defined by I.
  • step (603) the largest of the three pixel value difference sums is found and the index I corresponding to this largest value is identified as a block-edge position.
  • the steps (602) and (603) are then repeated for the remaining candidate edge positions identified in the process of Figure 5 to obtain a final set of block-edge positions.
  • W is a weighting factor
  • block-edge location process (316) may be helpful for the block-edge location process (316) to use pixel value differences evaluated over a pitch greater than two pixels.
  • the magnitudes of pixel value differences between the detected edge positions and the corresponding positions two pixels to the left are summed in a block edge-difference computation (317).
  • the sum is: The sum is: ⁇
  • the adjacent-pixel value differences for each block-interior region are averaged for each detected block in a block internal-difference computation (318).
  • the sum is: The sum is : ⁇
  • the detected block size is smaller than 6 the exclusion of values near to the detected edge position will result in all internal differences being excluded and so fewer values should be excluded in this case.
  • a block-artefact measure (320) for a region of an image is obtained by dividing the edge-difference sum from the edge-difference computation (317) by the internal difference sum from the internal difference sum (318) in the divider (318).
  • a region will be narrower than the full image width and less tall than the full image height. All the edge position detections that fall within the relevant region are included in the summations, so that a single edge which extends over several lines of the region will contribute to the summations on every image line included in the relevant region.
  • the division (318) can produce widely varying values for the block artefact measure (320). This effect can be reduced by adding a small value to the internal difference sum from the computation (318) and using this, slightly increased, value in the division (318).
  • a suitable value to add is the number of block edge detections within the relevant region; as for the summations, this will include multiple detections of the same edge on adjacent lines of the same region.
  • the block-artefact measure can be improved by weighting it according to the mean luminance of the relevant region, so that where the average luminance is very high or very low the artefact measure is attenuated. For example in a system where black is represented by the value 16 and white by 235, average luminance values less than 50 or greater than 170 would result in attenuation of the artefact measure. This weighting gives a result which better correlates with subjective block-artefact estimates.
  • a useful measure for a sequence of images is to sum the three highest, weighted regional block artefact measures for each image of the sequence and then to take a moving average (or other temporal low pass filter) of the result over several images of the sequence.
  • the processing of the autocorrelation result (306) to derive the block size output (311) could be achieved by taking the Fourier transform of the autocorrelation result (306), and finding the largest Fourier components in the range of spatial frequencies corresponding to expected block sizes.
  • the block presence flag (314) could also be found from the magnitudes of the Fourier components by comparing the magnitudes of the components corresponding to expected block sizes with the magnitudes of other components, whose frequencies are unlikely to be due to block artefacts. This approach is more computationally intensive than the system of Figure 3 , though if suitable resources are available it could be preferable.
  • the IIR filter (308), and the block edge difference internal difference summations (317) and (318) can be reset at shot changes to avoid combining data from unrelated images. This is only necessary if there is the possibility that the block structure of succeeding images is unrelated.
  • the invention may be used to analyse data corresponding to still or moving images, and the data may be derived from computer files or other storage media.
  • the time to analyse an image, or part of an image may be faster or slower than the length of time for which that image is intended to be presented to a viewer.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)
  • Testing, Inspecting, Measuring Of Stereoscopic Televisions And Televisions (AREA)

Claims (14)

  1. Vorrichtung zur Analyse von Bilddaten zur Quantifizierung von Artefakten aufgrund blockbasierter Verarbeitung, wobei die Vorrichtung Folgendes umfasst: ein räumliches Filter (2), das mit einem Satz von Pixelwerten arbeitet, die von den genannten Bilddaten abgeleitet werden, um niedrige räumliche Frequenzen zu entfernen; und einen Prozessor, der dafür konfiguriert ist, einen oder mehrere Beeinträchtigungsparameter aus den Größen der genannten gefilterten Werte abzuleiten, wobei der Prozessor dafür konfiguriert ist, einen Blockgrößenparameter aus der Analyse des räumlichen Frequenzspektrums der gefilterten Daten abzuleiten, dadurch gekennzeichnet, dass der Prozessor dafür konfiguriert ist, einen Blockgrößenparameter aus der Analyse einer Autokorrelationsfunktion der gefilterten Daten abzuleiten.
  2. Vorrichtung nach Anspruch 1, die ferner einen Gleichrichter (3) umfasst, der an dem Ausgang des räumlichen Filters arbeitet.
  3. Vorrichtung nach Anspruch 1 oder Anspruch 2, die zwei oder mehr alternative räumliche Filter und einen Selektor zum Auswählen der Ausgabe von einem der räumlichen Filter abhängig von einem Vergleich zwischen jeweiligen Filterausgaben umfasst.
  4. Vorrichtung nach einem der vorhergehenden Ansprüche, die ferner eine invertierte Coring-Funktion (302) umfasst.
  5. Vorrichtung nach einem der vorhergehenden Ansprüche, die für Folgendes konfiguriert ist: Vergleichen der Energie innerhalb eines Bandes von räumlichen Frequenzen einschließlich der räumlichen Frequenzen von erwarteten Blockgrößen mit der Energie außerhalb des genannten Bandes von räumlichen Frequenzen einschließlich der räumlichen Frequenzen von erwarteten Blockgrößen; und Kennzeichnen des Vorhandenseins von Blockartefakten, wenn die Energie innerhalb des Bandes von räumlichen Frequenzen einschließlich der räumlichen Frequenzen von erwarteten Blockgrößen die Energie außerhalb des genannten Bandes von räumlichen Frequenzen einschließlich der räumlichen Frequenzen um einen Schwellenwert übersteigt.
  6. Vorrichtung nach einem der vorhergehenden Ansprüche, die Folgendes umfasst: einen Summierer, um gefilterte und gleichgerichtete Daten vertikal über im Wesentlichen die volle Bildhöhe zu summieren, oder einen Summierer, um gefilterte und gleichgerichtete Daten horizontal über im Wesentlichen die volle Bildbreite zu summieren.
  7. Vorrichtung nach Anspruch 6, wobei Blockkantenpositionen durch die folgenden Schritte identifiziert werden:
    a. Addieren von Paaren von summierten gefilterten und gleichgerichteten Pixelwerten, die durch eine gemessene Blockgröße räumlich getrennt sind, um einen Satz von Additionsresultaten zu erhalten;
    b. Finden des Maximalwertes der Menge der Additionsergebnisse; und,
    c. Identifizieren der Position eines der Pixel, das zu dem Maximalwert des Satzes beiträgt, als Blockkantenposition.
  8. Vorrichtung nach Anspruch 7, wobei eine identifizierte Blockkantenposition durch folgende Schritte modifiziert wird:
    a. Bewerten von Pixelwert-Differenzgrößen zwischen Paaren von Pixeln, die mindestens zwei Pixel voneinander entfernt sind, wobei die Bewertung an der identifizierten Blockkantenposition und an Positionen auf jeder Seite der identifizierten Blockkantenposition durchgeführt wird;
    b. Testen der genannten Pixelwert-Differenzgrößen, um ein lokales Maximum zu identifizieren;
    c. wenn ein lokales Maximum existiert: Modifizieren der identifizierten Blockkantenposition, so dass sie mit der Position des lokalen Maximums übereinstimmt; und
    d. wenn kein lokales Maximum existiert: Verwerfen der identifizierten Blockkantenposition.
  9. Vorrichtung nach einem der vorhergehenden Ansprüche, wobei der Prozessor dafür konfiguriert ist, den Blockgrößenparameter aus dem Abstand zwischen Spitzenwerten in der genannten Autokorrelationsfunktion oder aus einer diskreten Cosinustransformation der genannten Autokorrelationsfunktion abzuleiten, wobei eine oder mehrere Basisfunktionen der genannten diskreten Cosinustransformation den erwarteten räumlichen Blockfrequenzen entsprechen.
  10. Vorrichtung nach einem der vorhergehenden Ansprüche, wobei Blockgrößenparameter von mehr als einem Bild vorzugsweise als Modalwert kombiniert werden.
  11. Verfahren zur Analyse von Bilddaten, die zuvor auf einer Blockbasis bearbeitet wurden, wobei das Verfahren folgende Schritte umfasst: Ableiten eines Satzes von Werten aus den Bilddaten; Berechnen einer Autokorrelationsfunktion für die Menge von Werten; und Ableiten aus der Autokorrelationsfunktion eines Blockgrößenparameters, der die vorherige Verarbeitung anzeigt.
  12. Verfahren nach Anspruch 11, wobei die genannte Autokorrelationsfunktion durch ein räumliches Bandpassfilter gefiltert wird.
  13. Verfahren nach Anspruch 11, wobei die genannte Autokorrelationsfunktion durch ein temporäres Tiefpassfilter gefiltert wird, das Daten von zwei oder mehr Bildern in einer Sequenz von Bildern kombiniert.
  14. Programmträger mit prozessorlesbaren Anweisungen zur Durchführung des Verfahrens nach einem der Ansprüche 11 bis 13.
EP07732500.9A 2006-04-21 2007-04-20 Bildanalyse Not-in-force EP2011080B1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB0607918A GB2437337A (en) 2006-04-21 2006-04-21 Measuring block artefacts in video data using an auto-correlation function
PCT/GB2007/001460 WO2007125286A2 (en) 2006-04-21 2007-04-20 Image analysis

Publications (2)

Publication Number Publication Date
EP2011080A2 EP2011080A2 (de) 2009-01-07
EP2011080B1 true EP2011080B1 (de) 2018-06-06

Family

ID=36581019

Family Applications (1)

Application Number Title Priority Date Filing Date
EP07732500.9A Not-in-force EP2011080B1 (de) 2006-04-21 2007-04-20 Bildanalyse

Country Status (5)

Country Link
US (1) US8094967B2 (de)
EP (1) EP2011080B1 (de)
CN (1) CN101438594B (de)
GB (1) GB2437337A (de)
WO (1) WO2007125286A2 (de)

Families Citing this family (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2437337A (en) * 2006-04-21 2007-10-24 Snell & Wilcox Ltd Measuring block artefacts in video data using an auto-correlation function
GB2457694B (en) 2008-02-21 2012-09-26 Snell Ltd Method of Deriving an Audio-Visual Signature
JP5130983B2 (ja) * 2008-03-25 2013-01-30 ソニー株式会社 画像処理装置および方法、並びにプログラム
CN101588191B (zh) * 2008-05-23 2013-03-27 华为技术有限公司 无线电信号认知方法及设备
JP5137687B2 (ja) * 2008-05-23 2013-02-06 キヤノン株式会社 復号装置及び復号方法、プログラム
US9131246B2 (en) * 2009-12-01 2015-09-08 Intel Corporation Detecting artifacts in quantization noise in images compresses using discrete cosine transforms
FR2959902B1 (fr) * 2010-05-04 2013-08-23 E2V Semiconductors Capteur d'image lineaire a defilement et sommation analogique et numerique et procede correspondant
GB2486483B (en) * 2010-12-16 2017-09-13 Snell Advanced Media Ltd Image analysis
US8891906B2 (en) * 2012-07-05 2014-11-18 Intel Corporation Pixel-adaptive interpolation algorithm for image upscaling
US9213781B1 (en) 2012-09-19 2015-12-15 Placemeter LLC System and method for processing image data
JP6533363B2 (ja) * 2012-12-14 2019-06-19 テクトロニクス・インコーポレイテッドＴｅｋｔｒｏｎｉｘ，Ｉｎｃ． アーチファクト検出方法及びビデオアーチファクト検出器
US9135720B2 (en) * 2013-03-27 2015-09-15 Stmicroelectronics Asia Pacific Pte. Ltd. Content-based aspect ratio detection
JP2017525064A (ja) 2014-05-30 2017-08-31 プレイスメーター インコーポレイテッドＰｌａｃｅｍｅｔｅｒ Ｉｎｃ． ビデオデータを用いた活動モニタリングのためのシステム及び方法
US11334751B2 (en) 2015-04-21 2022-05-17 Placemeter Inc. Systems and methods for processing video data for activity monitoring
US10043078B2 (en) 2015-04-21 2018-08-07 Placemeter LLC Virtual turnstile system and method
US11100335B2 (en) 2016-03-23 2021-08-24 Placemeter, Inc. Method for queue time estimation
CN108961210B (zh) * 2018-05-24 2021-08-31 上海集成电路研发中心有限公司 一种判断图像是否经过算法处理的方法
CN112749448B (zh) * 2019-10-31 2022-02-08 北京国联视讯信息技术股份有限公司 基于参数大数据辨识的空间测量系统以及方法

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1003335A2 (de) * 1998-11-18 2000-05-24 Tektronix, Inc. Effiziente Erkennung von Fehlerblöcken in einer auf DCT-Basis komprimierten Videosequenz
US6823089B1 (en) * 2000-09-28 2004-11-23 Eastman Kodak Company Method of determining the extent of blocking and contouring artifacts in a digital image

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5519774A (en) * 1992-12-08 1996-05-21 Bell Communications Research, Inc. Method and system for detecting at a selected station an alerting signal in the presence of speech
US5477465A (en) * 1993-08-31 1995-12-19 Talx Corporation Multi-frequency receiver with arbitrary center frequencies
US5819035A (en) * 1995-10-20 1998-10-06 Matsushita Electric Industrial Co., Ltd. Post-filter for removing ringing artifacts of DCT coding
KR100269125B1 (ko) * 1997-10-25 2000-10-16 윤덕용 양자화효과감소를위한영상데이터후처리방법및장치
US6101278A (en) * 1998-01-30 2000-08-08 Philips Electronics North America Corp. System for extracting coding parameters from video data
DE60022237T2 (de) * 1999-01-14 2006-07-06 Fuji Photo Film Co., Ltd., Minami-Ashigara Bidverarbeitungsverfahren und -System und Aufzeichnungsmedium zur Durchfürung des Verfahrens
EP1209624A1 (de) * 2000-11-27 2002-05-29 Sony International (Europe) GmbH Verfahren zur komprimiertbildlichen artefaktreduktion
US6873341B1 (en) * 2002-11-04 2005-03-29 Silicon Image, Inc. Detection of video windows and graphics windows
DE102006017280A1 (de) * 2006-04-12 2007-10-18 Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. Vorrichtung und Verfahren zum Erzeugen eines Umgebungssignals
GB2437337A (en) * 2006-04-21 2007-10-24 Snell & Wilcox Ltd Measuring block artefacts in video data using an auto-correlation function

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1003335A2 (de) * 1998-11-18 2000-05-24 Tektronix, Inc. Effiziente Erkennung von Fehlerblöcken in einer auf DCT-Basis komprimierten Videosequenz
US6823089B1 (en) * 2000-09-28 2004-11-23 Eastman Kodak Company Method of determining the extent of blocking and contouring artifacts in a digital image

Also Published As

Publication number Publication date
CN101438594A (zh) 2009-05-20
WO2007125286A2 (en) 2007-11-08
GB2437337A (en) 2007-10-24
US8094967B2 (en) 2012-01-10
EP2011080A2 (de) 2009-01-07
WO2007125286A3 (en) 2008-12-11
US20090103812A1 (en) 2009-04-23
GB0607918D0 (en) 2006-05-31
CN101438594B (zh) 2011-09-28

Similar Documents

Publication Publication Date Title
EP2011080B1 (de) Bildanalyse
US7663701B2 (en) Systems, methods, and apparatus for noise reduction
US8295633B2 (en) System and method for an adaptive de-blocking filter after decoding of compressed digital video
EP1865726A1 (de) Verfahren und Vorrichtung zum Messen des MPEG-Rauschpegels von komprimierten Digitalbildern
US6611295B1 (en) MPEG block detector
US9635308B2 (en) Preprocessing of interlaced video with overlapped 3D transforms
WO2004008780A1 (en) A method and apparatus for measuring the quality of video data
US8023765B2 (en) Block noise removal device
KR20110108918A (ko) 부호화된 영상의 확대비 및 노이즈 강도 추정장치 및 방법
US7974491B2 (en) Block noise removal device
US20100238354A1 (en) Method and system for adaptive noise reduction filtering
US20070285580A1 (en) Temporal noise analysis of a video signal
KR20060058703A (ko) 블럭 아티팩트 검출
EP2599311B1 (de) Erkennung von blockkomprimierungsartefakten bei digitalen videosignalen
US8743968B2 (en) Method and apparatus for analysing image data to quantify prior blockbased processing of the data
US8553988B2 (en) Objective picture quality measurement
KR100950969B1 (ko) 영상의 블록킹 현상 제거 시스템 및 그 방법
Yang et al. Research on Video Quality Assessment.
Qadri et al. Frequency domain blockiness and blurriness meter for image quality assessment
Hasan et al. Blocking artifact detection by analyzing the distortions of local properties in images

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

17P Request for examination filed

Effective date: 20081030

AK Designated contracting states

Kind code of ref document: A2

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LI LT LU LV MC MT NL PL PT RO SE SI SK TR

AX Request for extension of the european patent

Extension state: AL BA HR MK RS

R17D Deferred search report published (corrected)

Effective date: 20081211

RIC1 Information provided on ipc code assigned before grant

Ipc: H04N 7/26 20060101AFI20090213BHEP

RAP1 Party data changed (applicant data changed or rights of an application transferred)

Owner name: SNELL LIMITED

DAX Request for extension of the european patent (deleted)
RAP1 Party data changed (applicant data changed or rights of an application transferred)

Owner name: SNELL ADVANCED MEDIA LIMITED

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: EXAMINATION IS IN PROGRESS

17Q First examination report despatched

Effective date: 20170719

REG Reference to a national code

Ref country code: DE

Ref legal event code: R079

Ref document number: 602007055041

Country of ref document: DE

Free format text: PREVIOUS MAIN CLASS: G06T0007000000

Ipc: H04N0019600000

GRAP Despatch of communication of intention to grant a patent

Free format text: ORIGINAL CODE: EPIDOSNIGR1

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: GRANT OF PATENT IS INTENDED

RIC1 Information provided on ipc code assigned before grant

Ipc: H04N 19/86 20140101ALI20171222BHEP

Ipc: H04N 19/60 20140101AFI20171222BHEP

Ipc: H04N 19/61 20140101ALI20171222BHEP

INTG Intention to grant announced

Effective date: 20180125

GRAS Grant fee paid

Free format text: ORIGINAL CODE: EPIDOSNIGR3

GRAA (expected) grant

Free format text: ORIGINAL CODE: 0009210

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE PATENT HAS BEEN GRANTED

AK Designated contracting states

Kind code of ref document: B1

Designated state(s): AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HU IE IS IT LI LT LU LV MC MT NL PL PT RO SE SI SK TR

REG Reference to a national code

Ref country code: GB

Ref legal event code: FG4D

RIN1 Information on inventor provided before grant (corrected)

Inventor name: DIGGINS, JONATHAN

REG Reference to a national code

Ref country code: CH

Ref legal event code: EP

Ref country code: AT

Ref legal event code: REF

Ref document number: 1007329

Country of ref document: AT

Kind code of ref document: T

Effective date: 20180615

REG Reference to a national code

Ref country code: IE

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: DE

Ref legal event code: R096

Ref document number: 602007055041

Country of ref document: DE

REG Reference to a national code

Ref country code: NL

Ref legal event code: MP

Effective date: 20180606

REG Reference to a national code

Ref country code: LT

Ref legal event code: MG4D

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: CY

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: BG

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180906

Ref country code: FI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: LT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: ES

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: GR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180907

Ref country code: LV

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

REG Reference to a national code

Ref country code: AT

Ref legal event code: MK05

Ref document number: 1007329

Country of ref document: AT

Kind code of ref document: T

Effective date: 20180606

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: RO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: CZ

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: PL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20181006

Ref country code: EE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: AT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: SK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

REG Reference to a national code

Ref country code: CH

Ref legal event code: PK

Free format text: BERICHTIGUNGEN

RIC2 Information provided on ipc code assigned after grant

Ipc: H04N 19/86 20140101ALI20171222BHEP

Ipc: H04N 19/60 20140101AFI20171222BHEP

Ipc: H04N 19/61 20140101ALI20171222BHEP

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

REG Reference to a national code

Ref country code: DE

Ref legal event code: R097

Ref document number: 602007055041

Country of ref document: DE

PLBE No opposition filed within time limit

Free format text: ORIGINAL CODE: 0009261

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT

26N No opposition filed

Effective date: 20190307

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

Ref country code: DK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

REG Reference to a national code

Ref country code: CH

Ref legal event code: PL

REG Reference to a national code

Ref country code: BE

Ref legal event code: MM

Effective date: 20190430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LU

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190420

Ref country code: MC

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LI

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

Ref country code: CH

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: FR

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

Ref country code: BE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190430

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: TR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20190420

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: PT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20181008

REG Reference to a national code

Ref country code: DE

Ref legal event code: R081

Ref document number: 602007055041

Country of ref document: DE

Owner name: GRASS VALLEY LIMITED, NEWBURY, GB

Free format text: FORMER OWNER: SNELL ADVANCED MEDIA LIMITED, NEWBURY, GB

Ref country code: DE

Ref legal event code: R082

Ref document number: 602007055041

Country of ref document: DE

Representative=s name: ZACCO PATENTANWALTS- UND RECHTSANWALTSGESELLSC, DE

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: DE

Payment date: 20200429

Year of fee payment: 14

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: GB

Payment date: 20200427

Year of fee payment: 14

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: HU

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT; INVALID AB INITIO

Effective date: 20070420

Ref country code: MT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20180606

REG Reference to a national code

Ref country code: DE

Ref legal event code: R119

Ref document number: 602007055041

Country of ref document: DE

GBPC Gb: european patent ceased through non-payment of renewal fee

Effective date: 20210420

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: DE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20211103

Ref country code: GB

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20210420